data <- read_csv("diabetes.csv")
## Rows: 768 Columns: 9
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## dbl (9): Pregnancies, Glucose, BloodPressure, SkinThickness, Insulin, BMI, D...
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
colnames(data)
## [1] "Pregnancies" "Glucose"
## [3] "BloodPressure" "SkinThickness"
## [5] "Insulin" "BMI"
## [7] "DiabetesPedigreeFunction" "Age"
## [9] "Outcome"
data
## # A tibble: 768 × 9
## Pregnancies Glucose BloodPressure SkinThickness Insulin BMI
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 6 148 72 35 0 33.6
## 2 1 85 66 29 0 26.6
## 3 8 183 64 0 0 23.3
## 4 1 89 66 23 94 28.1
## 5 0 137 40 35 168 43.1
## 6 5 116 74 0 0 25.6
## 7 3 78 50 32 88 31
## 8 10 115 0 0 0 35.3
## 9 2 197 70 45 543 30.5
## 10 8 125 96 0 0 0
## # ℹ 758 more rows
## # ℹ 3 more variables: DiabetesPedigreeFunction <dbl>, Age <dbl>, Outcome <dbl>
test <- na.omit(data)
test
## # A tibble: 768 × 9
## Pregnancies Glucose BloodPressure SkinThickness Insulin BMI
## <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 6 148 72 35 0 33.6
## 2 1 85 66 29 0 26.6
## 3 8 183 64 0 0 23.3
## 4 1 89 66 23 94 28.1
## 5 0 137 40 35 168 43.1
## 6 5 116 74 0 0 25.6
## 7 3 78 50 32 88 31
## 8 10 115 0 0 0 35.3
## 9 2 197 70 45 543 30.5
## 10 8 125 96 0 0 0
## # ℹ 758 more rows
## # ℹ 3 more variables: DiabetesPedigreeFunction <dbl>, Age <dbl>, Outcome <dbl>
colnames(test)
## [1] "Pregnancies" "Glucose"
## [3] "BloodPressure" "SkinThickness"
## [5] "Insulin" "BMI"
## [7] "DiabetesPedigreeFunction" "Age"
## [9] "Outcome"
heatmaply_cor(x = cor(test), xlab = "Features",
ylab = "Features", k_col = 2, k_row = 2)
## Warning in doTryCatch(return(expr), name, parentenv, handler): unable to load shared object '/Library/Frameworks/R.framework/Resources/modules//R_X11.so':
## dlopen(/Library/Frameworks/R.framework/Resources/modules//R_X11.so, 0x0006): Library not loaded: /opt/X11/lib/libSM.6.dylib
## Referenced from: <B3716E5A-BF4D-3CA3-B8EB-89643DB72A04> /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/modules/R_X11.so
## Reason: tried: '/opt/X11/lib/libSM.6.dylib' (no such file), '/System/Volumes/Preboot/Cryptexes/OS/opt/X11/lib/libSM.6.dylib' (no such file), '/opt/X11/lib/libSM.6.dylib' (no such file), '/Library/Frameworks/R.framework/Resources/lib/libSM.6.dylib' (no such file), '/Library/Java/JavaVirtualMachines/jdk-11.0.18+10/Contents/Home/lib/server/libSM.6.dylib' (no such file)
cor_matrix <- cor(test)
print(cor_matrix)
## Pregnancies Glucose BloodPressure SkinThickness
## Pregnancies 1.00000000 0.12945867 0.14128198 -0.08167177
## Glucose 0.12945867 1.00000000 0.15258959 0.05732789
## BloodPressure 0.14128198 0.15258959 1.00000000 0.20737054
## SkinThickness -0.08167177 0.05732789 0.20737054 1.00000000
## Insulin -0.07353461 0.33135711 0.08893338 0.43678257
## BMI 0.01768309 0.22107107 0.28180529 0.39257320
## DiabetesPedigreeFunction -0.03352267 0.13733730 0.04126495 0.18392757
## Age 0.54434123 0.26351432 0.23952795 -0.11397026
## Outcome 0.22189815 0.46658140 0.06506836 0.07475223
## Insulin BMI DiabetesPedigreeFunction
## Pregnancies -0.07353461 0.01768309 -0.03352267
## Glucose 0.33135711 0.22107107 0.13733730
## BloodPressure 0.08893338 0.28180529 0.04126495
## SkinThickness 0.43678257 0.39257320 0.18392757
## Insulin 1.00000000 0.19785906 0.18507093
## BMI 0.19785906 1.00000000 0.14064695
## DiabetesPedigreeFunction 0.18507093 0.14064695 1.00000000
## Age -0.04216295 0.03624187 0.03356131
## Outcome 0.13054795 0.29269466 0.17384407
## Age Outcome
## Pregnancies 0.54434123 0.22189815
## Glucose 0.26351432 0.46658140
## BloodPressure 0.23952795 0.06506836
## SkinThickness -0.11397026 0.07475223
## Insulin -0.04216295 0.13054795
## BMI 0.03624187 0.29269466
## DiabetesPedigreeFunction 0.03356131 0.17384407
## Age 1.00000000 0.23835598
## Outcome 0.23835598 1.00000000
summary(test)
## Pregnancies Glucose BloodPressure SkinThickness
## Min. : 0.000 Min. : 0.0 Min. : 0.00 Min. : 0.00
## 1st Qu.: 1.000 1st Qu.: 99.0 1st Qu.: 62.00 1st Qu.: 0.00
## Median : 3.000 Median :117.0 Median : 72.00 Median :23.00
## Mean : 3.845 Mean :120.9 Mean : 69.11 Mean :20.54
## 3rd Qu.: 6.000 3rd Qu.:140.2 3rd Qu.: 80.00 3rd Qu.:32.00
## Max. :17.000 Max. :199.0 Max. :122.00 Max. :99.00
## Insulin BMI DiabetesPedigreeFunction Age
## Min. : 0.0 Min. : 0.00 Min. :0.0780 Min. :21.00
## 1st Qu.: 0.0 1st Qu.:27.30 1st Qu.:0.2437 1st Qu.:24.00
## Median : 30.5 Median :32.00 Median :0.3725 Median :29.00
## Mean : 79.8 Mean :31.99 Mean :0.4719 Mean :33.24
## 3rd Qu.:127.2 3rd Qu.:36.60 3rd Qu.:0.6262 3rd Qu.:41.00
## Max. :846.0 Max. :67.10 Max. :2.4200 Max. :81.00
## Outcome
## Min. :0.000
## 1st Qu.:0.000
## Median :0.000
## Mean :0.349
## 3rd Qu.:1.000
## Max. :1.000
ggplot(test, aes(test$Outcome, fill = test$Outcome, color = Outcome)) +
geom_bar() +
labs(title = "Diabetes Outcome", x = "Diabetes") +
geom_text(stat = "count", aes(label = ..count..), vjust = -0.5) +
theme(plot.title = element_text(hjust = 0.5))
## Warning: Use of `test$Outcome` is discouraged.
## ℹ Use `Outcome` instead.
## Use of `test$Outcome` is discouraged.
## ℹ Use `Outcome` instead.
## Warning: The dot-dot notation (`..count..`) was deprecated in ggplot2 3.4.0.
## ℹ Please use `after_stat(count)` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Warning: Use of `test$Outcome` is discouraged.
## ℹ Use `Outcome` instead.
## Use of `test$Outcome` is discouraged.
## ℹ Use `Outcome` instead.
## Warning: The following aesthetics were dropped during statistical transformation: fill,
## colour
## ℹ This can happen when ggplot fails to infer the correct grouping structure in
## the data.
## ℹ Did you forget to specify a `group` aesthetic or to convert a numerical
## variable into a factor?
## The following aesthetics were dropped during statistical transformation: fill,
## colour
## ℹ This can happen when ggplot fails to infer the correct grouping structure in
## the data.
## ℹ Did you forget to specify a `group` aesthetic or to convert a numerical
## variable into a factor?
df <- test %>%
gather(key = "variable", value = "value")
# Plot the distribution of all columns in one graph
ggplot(df, aes(x = value, fill = variable)) +
geom_density(alpha = 0.5) +
labs(title = "Distribution of All Columns",
x = "Value",
y = "Density") +
theme_minimal() +
ylim(c(0, 0.2)) +
xlim(c(0, 250))
## Warning: Removed 56 rows containing non-finite values (`stat_density()`).
# Calculate skewness for each column
skewness_values <- sapply(test, skewness)
# Print the skewness values
print(skewness_values)
## Pregnancies Glucose BloodPressure
## 0.8981549 0.1730754 -1.8364126
## SkinThickness Insulin BMI
## 0.1089456 2.2633826 -0.4273073
## DiabetesPedigreeFunction Age Outcome
## 1.9124179 1.1251880 0.6325383
# Separate glucose levels for diabetic and non-diabetic individuals
blood_pressure_age_lt_30 <- test$BloodPressure[test$Age <= 30]
blood_pressure_age_gt_30 <- test$BloodPressure[test$Age > 30]
t_test_result <- t.test(blood_pressure_age_lt_30, blood_pressure_age_gt_30)
print(t_test_result)
##
## Welch Two Sample t-test
##
## data: blood_pressure_age_lt_30 and blood_pressure_age_gt_30
## t = -6.0637, df = 755.07, p-value = 2.101e-09
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
## -10.953401 -5.595698
## sample estimates:
## mean of x mean of y
## 65.32374 73.59829
cor_test_result <- cor.test(test$Age, test$BloodPressure)
print(cor_test_result)
##
## Pearson's product-moment correlation
##
## data: test$Age and test$BloodPressure
## t = 6.8281, df = 766, p-value = 1.752e-11
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.1716931 0.3051022
## sample estimates:
## cor
## 0.2395279
test1 <- subset(test, BloodPressure != 0)
# Scatter plot with color based on another variable
ggplot(test1, aes(x = Age, y = BloodPressure, color = Outcome)) +
geom_point() +
labs(title = "Scatter Plot of BloodPressure vs. Age",
x = "Age",
y = "BloodPressure",
color = "Outcome") +
geom_smooth(method = "lm", se = TRUE, aes(group = 1)) +
annotate("text", x = Inf, y = Inf, hjust = 1, vjust = 1,
label = paste("Regression Coefficient: ",
round(coef(lm(Age ~ BloodPressure, data = data))[2], 4)),
color = "red")
## `geom_smooth()` using formula = 'y ~ x'
## Warning: The following aesthetics were dropped during statistical transformation: colour
## ℹ This can happen when ggplot fails to infer the correct grouping structure in
## the data.
## ℹ Did you forget to specify a `group` aesthetic or to convert a numerical
## variable into a factor?
theme_minimal()
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## ..$ size : NULL
## ..$ hjust : NULL
## ..$ vjust : NULL
## ..$ angle : num 90
## ..$ lineheight : NULL
## ..$ margin : NULL
## ..$ debug : NULL
## ..$ inherit.blank: logi TRUE
## ..- attr(*, "class")= chr [1:2] "element_text" "element"
## $ strip.text.y.right : NULL
## $ strip.switch.pad.grid : 'simpleUnit' num 2.75points
## ..- attr(*, "unit")= int 8
## $ strip.switch.pad.wrap : 'simpleUnit' num 2.75points
## ..- attr(*, "unit")= int 8
## - attr(*, "class")= chr [1:2] "theme" "gg"
## - attr(*, "complete")= logi TRUE
## - attr(*, "validate")= logi TRUE